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A two-stage framework for transformer maintenance management is introduced and formulated in Part I of this two-part paper in the context of transmission asset management strategies (TAMS). The proposed model optimizes maintenance outage schedule over a predefined period of time by taking into account the actual and expected transformer assets' condition dynamics in terms of failure rate and resource limitations in midterm horizons, as well as operating constraints, economic considerations and N-1 reliability in the shorter term. In Part II, a small six-bus system is first used to demonstrate how the two-stage maintenance framework works using a step-by-step procedure. Then, IEEE-RTS is used to investigate the performance of the proposed model in more detail. In addition, the impacts of varying the characteristics of the proposed midterm and short-term maintenance schedulers, such as flexibility in time horizon selection, on maintenance scheduling results and computational efficiency are investigated on IEEE-RTS. The numerical studies indicate that the proposed framework gives appropriate results in terms of economics and technical constraints at a reasonable computational cost. [ABSTRACT FROM PUBLISHER]

By the introduction of competitive supply, modern electric utilities are forced to operate their systems closer to their security limits. Under such fragile conditions, any disturbance could endanger system security and lead to system collapse. There is, therefore, a need to develop new methods which could evaluate optimal scheduling of operating reserve and forewarn the system operators to take necessary preventive actions in case need arises. An effective method is proposed in this paper to optimally allocate spinning reserve based on a well-being model. The method used in conventional well-being framework for classifying power system comfort zone into healthy and marginal states is initially revised. The optimal value of health index and system spinning reserve requirements are then evaluated on the basis of a trade off between the total cost of spinning reserve and the expected cost of energy not served. The effectiveness of the proposed method is examined using the IEEE-RTS. [ABSTRACT FROM AUTHOR]